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Multiobjective image recognition algorithm in the fully automatic die bonder

JIANG Kai, CHEN Hai-xia, YUAN Sen-miao

《机械工程前沿（英文）》 2006年第1卷第3期页码 313-316 doi: 10.1007/s11465-006-0026-y

摘要： It is a very important task to automatically fix the number of die in the image recognition system of a fully automatic die bonder. A multiobjective image recognition algorithm based on clustering Genetic Algorithm (GA), is proposed in this paper. In the evolutionary process of GA, a clustering method is provided that utilizes information from the template and the fitness landscape of the current population. The whole population is grouped into different niches by the clustering method. Experimental results demonstrated that the number of target images could be determined by the algorithm automatically, and multiple targets could be recognized at a time. As a result, time consumed by one image recognition is shortened, the performance of the image recognition system is improved, and the atomization of the system is fulfilled.

关键词： clustering different recognition algorithm Algorithm multiobjective

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Advances in tissue state recognition in spinal surgery: a review

Hao Qu, Yu Zhao

《医学前沿（英文）》 2021年第15卷第4期页码 575-584 doi: 10.1007/s11684-020-0816-3

摘要： Spinal disease is an important cause of cervical discomfort, low back pain, radiating pain in the limbs, and neurogenic intermittent claudication, and its incidence is increasing annually. From the etiological viewpoint, these symptoms are directly caused by the compression of the spinal cord, nerve roots, and blood vessels and are most effectively treated with surgery. Spinal surgeries are primarily performed using two different techniques: spinal canal decompression and internal fixation. In the past, tactile sensation was the primary method used by surgeons to understand the state of the tissue within the operating area. However, this method has several disadvantages because of its subjectivity. Therefore, it has become the focus of spinal surgery research so as to strengthen the objectivity of tissue state recognition, improve the accuracy of safe area location, and avoid surgical injury to tissues. Aside from traditional imaging methods, surgical sensing techniques based on force, bioelectrical impedance, and other methods have been gradually developed and tested in the clinical setting. This article reviews the progress of different tissue state recognition methods in spinal surgery and summarizes their advantages and disadvantages.

关键词： spinal surgery tissue state recognition image force sensing bioelectrical impedance

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Diagnosis of sewer pipe defects on image recognition of multi-features and support vector machine in

Xiangyang Ye, Jian’e Zuo, Ruohan Li, Yajiao Wang, Lili Gan, Zhonghan Yu, Xiaoqing Hu

《环境科学与工程前沿（英文）》 2019年第13卷第2期 doi: 10.1007/s11783-019-1102-y

摘要：

An image-recognition-based diagnosis system of pipe defect types was established.

1043 practical pipe images were gathered by CCTV robot in a southern Chinese city.

The overall accuracy of the system is 84% and the highest accuracy is 99.3%.

The accuracy shows positive correlation to the number of training samples.

关键词： Sewer pipe defects Defect diagnosing Image recognition Multi-features extraction Support vector machine

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基于光谱辐射信息的高温目标图像识别

范学良,程晓舫,许军

《中国工程科学》 2004年第6卷第6期页码 57-62

摘要：

利用光学及辐射度学的基本原理，对成像过程进行理论分析，建立了照明条件下识别视场中高温目标的数学模型，揭示了影响识别效果的各物理因素。通过对这些物理因素进行分析，指出“切割波段”可有效提高信噪比，将高温目标识别出来，并通过液晶光阀予以技术实现。实验结果验证了该方案的可行性及有效性。

关键词： CCD影像目标识别辐射信息液晶光阀

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Optimal CNN-based semantic segmentation model of cutting slope images

Mansheng LIN; Shuai TENG; Gongfa CHEN; Jianbing LV; Zhongyu HAO

《结构与土木工程前沿（英文）》 2022年第16卷第4期页码 414-433 doi: 10.1007/s11709-021-0797-6

摘要： This paper utilizes three popular semantic segmentation networks, specifically DeepLab v3+, fully convolutional network (FCN), and U-Net to qualitively analyze and identify the key components of cutting slope images in complex scenes and achieve rapid image-based slope detection. The elements of cutting slope images are divided into 7 categories. In order to determine the best algorithm for pixel level classification of cutting slope images, the networks are compared from three aspects: a) different neural networks, b) different feature extractors, and c) 2 different optimization algorithms. It is found that DeepLab v3+ with Resnet18 and Sgdm performs best, FCN 32s with Sgdm takes the second, and U-Net with Adam ranks third. This paper also analyzes the segmentation strategies of the three networks in terms of feature map visualization. Results show that the contour generated by DeepLab v3+ (combined with Resnet18 and Sgdm) is closest to the ground truth, while the resulting contour of U-Net (combined with Adam) is closest to the input images.

关键词： slope damage image recognition semantic segmentation feature map visualizations

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Turbidity-adaptive underwater image enhancement method using image fusion

《机械工程前沿（英文）》 2022年第17卷第3期 doi: 10.1007/s11465-021-0669-8

摘要： Clear, correct imaging is a prerequisite for underwater operations. In real freshwater environment including rivers and lakes, the water bodies are usually turbid and dynamic, which brings extra troubles to quality of imaging due to color deviation and suspended particulate. Most of the existing underwater imaging methods focus on relatively clear underwater environment, it is uncertain that if those methods can work well in turbid and dynamic underwater environments. In this paper, we propose a turbidity-adaptive underwater image enhancement method. To deal with attenuation and scattering of varying degree, the turbidity is detected by the histogram of images. Based on the detection result, different image enhancement strategies are designed to deal with the problem of color deviation and blurring. The proposed method is verified by an underwater image dataset captured in real underwater environment. The result is evaluated by image metrics including structure similarity index measure, underwater color image quality evaluation metric, and speeded-up robust features. Test results exhibit that the method can correct the color deviation and improve the quality of underwater images.

关键词： turbidity underwater image enhancement image fusion underwater robots visibility

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Gradient-based compressive image fusion

Yang CHEN,Zheng QIN

《信息与电子工程前沿（英文）》 2015年第16卷第3期页码 227-237 doi: 10.1631/FITEE.1400217

摘要： We present a novel image fusion scheme based on gradient and scrambled block Hadamard ensemble (SBHE) sampling for compressive sensing imaging. First, source images are compressed by compressive sensing, to facilitate the transmission of the sensor. In the fusion phase, the image gradient is calculated to reflect the abundance of its contour information. By compositing the gradient of each image, gradient-based weights are obtained, with which compressive sensing coefficients are achieved. Finally, inverse transformation is applied to the coefficients derived from fusion, and the fused image is obtained. Information entropy (IE), Xydeas’s and Piella’s metrics are applied as non-reference objective metrics to evaluate the fusion quality in line with different fusion schemes. In addition, different image fusion application scenarios are applied to explore the scenario adaptability of the proposed scheme. Simulation results demonstrate that the gradient-based scheme has the best performance, in terms of both subjective judgment and objective metrics. Furthermore, the gradient-based fusion scheme proposed in this paper can be applied in different fusion scenarios.

关键词： Compressive sensing (CS) Image fusion Gradient-based image fusion CS-based image fusion

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Edge detection of steel plates at high temperature using image measurement

Qiong Zhou, Qi An

《机械工程前沿（英文）》 2009年第4卷第1期页码 77-82 doi: 10.1007/s11465-009-0013-1

摘要： An edge detection method for the measurement of steel plate’s thermal expansion is proposed in this paper, where the shrinkage of a steel plate is measured when temperature drops. First, images are picked up by an imaging system; a method of regional edge detection based on grayscales’ sudden change is then applied to detect the edges of the steel plate; finally, pixel coordinates of the edge position are transformed to physical coordinates through calibration parameters. The experiment shows that the real-time, high precision, and non-contact measurement of the steel plate’s edge position under high temperature can be realized using the imaging measurement method established in this paper.

关键词： thermal expansion image measurement edge detection image calibration

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View-invariant human action recognition via robust locally adaptive multi-view learning

Jia-geng FENG,Jun XIAO

《信息与电子工程前沿（英文）》 2015年第16卷第11期页码 917-920 doi: 10.1631/FITEE.1500080

摘要： Human action recognition is currently one of the most active research areas in computer vision. It has been widely used in many applications, such as intelligent surveillance, perceptual interface, and content-based video retrieval. However, some extrinsic factors are barriers for the development of action recognition; e.g., human actions may be observed from arbitrary camera viewpoints in realistic scene. Thus, view-invariant analysis becomes important for action recognition algorithms, and a number of researchers have paid much attention to this issue. In this paper, we present a multi-view learning approach to recognize human actions from different views. As most existing multi-view learning algorithms often suffer from the problem of lacking data adaptiveness in the nearest neighborhood graph construction procedure, a robust locally adaptive multi-view learning algorithm based on learning multiple local L1-graphs is proposed. Moreover, an efficient iterative optimization method is proposed to solve the proposed objective function. Experiments on three public view-invariant action recognition datasets, i.e., ViHASi, IXMAS, and WVU, demonstrate data adaptiveness, effectiveness, and efficiency of our algorithm. More importantly, when the feature dimension is correctly selected (i.e.,>60), the proposed algorithm stably outperforms state-of-the-art counterparts and obtains about 6% improvement in recognition accuracy on the three datasets.

关键词： View-invariant Action recognition Multi-view learning L1-norm Local learning

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Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

《环境科学与工程前沿（英文）》 2021年第15卷第6期 doi: 10.1007/s11783-021-1430-6

摘要：

• UV-vis absorption analyzer was applied in drainage type online recognition.

关键词： Drainage online recognition UV-vis spectra Derivative spectrum Convolutional neural network

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Face recognition based on subset selection via metric learning on manifold

Hong SHAO,Shuang CHEN,Jie-yi ZHAO,Wen-cheng CUI,Tian-shu YU

《信息与电子工程前沿（英文）》 2015年第16卷第12期页码 1046-1058 doi: 10.1631/FITEE.1500085

摘要： With the development of face recognition using sparse representation based classification (SRC), many relevant methods have been proposed and investigated. However, when the dictionary is large and the representation is sparse, only a small proportion of the elements contributes to the 1-minimization. Under this observation, several approaches have been developed to carry out an efficient element selection procedure before SRC. In this paper, we employ a metric learning approach which helps find the active elements correctly by taking into account the interclass/intraclass relationship and manifold structure of face images. After the metric has been learned, a neighborhood graph is constructed in the projected space. A fast marching algorithm is used to rapidly select the subset from the graph, and SRC is implemented for classification. Experimental results show that our method achieves promising performance and significant efficiency enhancement.

关键词： Face recognition Sparse representation Manifold structure Metric learning Subset selection

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激活–效价维度空间中基于脸部图像的情感等级排序方法 None

Guo-peng XU, Hai-tang LU, Fei-fei ZHANG, Qi-rong MAO

《信息与电子工程前沿（英文）》 2018年第19卷第6期页码 783-795 doi: 10.1631/FITEE.1700270

摘要：在维度情感识别领域，分类和回归通常被用来对情感的机器学习进行建模和预测。然而，在维度情感空间中，情感标注通常是一个连续的实数值，拥有有序属性。而前面所提的两种方法并没有考虑并利用这一重要信息。因此，我们提出一个在激活和效价维度空间下的基于脸部图像的情感等级排序框架。我们的方法能够通过离散化连续的情感标注得到情感等级，并恰当地利用它们之间的有序信息。确切地说，首先训练一系列基本误差敏感二分类器，每个二分类器都使用经过二值重新标注的全部样本。依据样本对应的情感等级与给定二分类器对应的情感等级的比较结果，对二值进行重新标注。然后通过聚合所有二分类器的输出结果，可以得到样本最终的情感等级预测结果。在AVEC 2015挑战赛标准数据集和SEMAINE子集数据集上对所提方法与基本的和基于深度学习的分类和回归方法进行比较。实验结果表明，所提出的基于排序的情感识别方法在激活和效价两个维度上都是有效的。

关键词：有序排序；维度情感识别；效价度；激活度；脸部图像处理

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Deformable image registration with geometric changes

Yu LIU,Bo ZHU

《信息与电子工程前沿（英文）》 2015年第16卷第10期页码 829-837 doi: 10.1631/FITEE.1500045

摘要： Geometric changes present a number of difficulties in deformable image registration. In this paper, we propose aglobal deformation framework to model geometric changes whilst promoting a smooth transformation between source and target images. To achieve this, we have developed an innovative model which significantly reduces the side effects of geometric changes in image registration, and thus improves the registration accuracy. Our key contribution is the introduction of a sparsity-inducing norm, which is typically L1 norm regularization targeting regions where geometric changes occur. This preserves the smoothness of global transformation by eliminating local transformation under different conditions. Numerical solutions are discussed and analyzed to guarantee the stability and fast convergence of our algorithm. To demonstrate the effectiveness and utility of this method, we evaluate it on both synthetic data and real data from traumatic brain injury (TBI). We show that the transformation estimated from our model is able to reconstruct the target image with lower instances of error than a standard elastic registration model.

关键词： Geometric changes Image registration Sparsity Traumatic brain injury (TBI)

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Named entity recognition for Chinese construction documents based on conditional random field

《工程管理前沿（英文）》 2023年第10卷第2期页码 237-249 doi: 10.1007/s42524-021-0179-8

摘要： Named entity recognition (NER) is essential in many natural language processing (NLP) tasks such as information extraction and document classification. A construction document usually contains critical named entities, and an effective NER method can provide a solid foundation for downstream applications to improve construction management efficiency. This study presents a NER method for Chinese construction documents based on conditional random field (CRF), including a corpus design pipeline and a CRF model. The corpus design pipeline identifies typical NER tasks in construction management, enables word-based tokenization, and controls the annotation consistency with a newly designed annotating specification. The CRF model engineers nine transformation features and seven classes of state features, covering the impacts of word position, part-of-speech (POS), and word/character states within the context. The F1-measure on a labeled construction data set is 87.9%. Furthermore, as more domain knowledge features are infused, the marginal performance improvement of including POS information will decrease, leading to a promising research direction of POS customization to improve NLP performance with limited data.

关键词： NER NLP Chinese language construction document

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Visual chiral recognition of 1,1′-binaphthol through enantioselective collapse of gel based on an amphiphilic

Xuhong Zhang, Haimiao Li, Xin Zhang, Meng An, Weiwei Fang, Haitao Yu

《化学科学与工程前沿（英文）》 2017年第11卷第2期页码 231-237 doi: 10.1007/s11705-017-1633-3

摘要： A novel gelator that contained both Schiff base and L-lysine moieties was synthesized and its gelation behavior was tested. This gelator can form gels in various organic solvents. The resulting gel can be applied as a fascinating platform for visual recognition of enantiomeric 1-(2-hydroxynaphthalen-1-yl)naphthalen-2-ol (BINOL) through selective gel collapse. In addition, the mechanism for the reaction of the gel with chiral BINOL was investigated by scanning electron microscope and H nuclear magnetic resonance.

关键词： gelator Schiff base chiral recognition gel formation gel collapse